[Pre – Learning] BSCS_AIE 481: Deep Learning and Neural Networks
About Course
This course provides an in-depth study of neural network architectures and their applications in deep learning.
Students will explore the theoretical foundations of neural networks, learn to implement various architectures such as convolutional and recurrent neural networks, and apply these models to real-world tasks like image recognition, natural language processing, and more.
Course Content
Topic 1: Introduction to Neural Networks
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LO1: Define the basic concepts and architecture of neural networks.
09:42 -
LO2: Explain the biological inspiration and functioning of artificial neural networks.
00:00 -
LO3: Identify the key components of a neural network architecture.
00:00 -
Knowledge Check
